US2024406410A1PendingUtilityA1

Method for processing video signal by using local illumination compensation (lic) mode, and apparatus therefor

Assignee: WILUS INST STANDARDS & TECH INCPriority: Sep 3, 2021Filed: Sep 5, 2022Published: Dec 5, 2024
Est. expirySep 3, 2041(~15.1 yrs left)· nominal 20-yr term from priority
H04N 19/593H04N 19/157H04N 19/42H04N 19/132H04N 19/117H04N 19/176H04N 19/186H04N 19/105H04N 19/70H04N 19/119H04N 19/50H04N 19/96H04N 19/51H04N 19/503
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Claims

Abstract

An apparatus for decoding a video signal comprises a processor, wherein the processor parses a first syntax element that is a general constraint information (GCI) syntax element, parses a second syntax element that indicates whether an LIC mode is available for a current sequence, and parses a third syntax element that indicates whether the LIC mode is used in a current block on the basis of a parsing result of the second syntax element.

Claims

exact text as granted — not AI-modified
1 - 20 . (canceled) 
     
     
         21 . A device for decoding a video signal, the device comprising a processor,
 wherein the processor is configured to:   configure a first template including neighboring blocks of a current block,   configure a second template including neighboring blocks of a reference block of the current block,   obtain a convolutional model based on the first template and the second template, predict the current block based on the convolutional model.   
     
     
         22 . The device of  claim 21 ,
 wherein a first color component of samples of the first template and a second color component of samples of the second template for the convolutional model are the same.   
     
     
         23 . The device of  claim 22 ,
 wherein the first color component and the second color component are a luma component.   
     
     
         24 . The device of  claim 21 ,
 wherein a filter coefficient of the convolutional model is a coefficient for at least one sample among a upper sample, a lower sample, a left sample, or a right sample of a first sample of the current block.   
     
     
         25 . The device of  claim 24 ,
 when one or more the upper sample, the lower sample, the left sample, the right sample of the first sample is not included in the first template,   a value of the sample not included in the first template is the same as a value of a sample closet to a sample not included in the first template among samples included in the first template.   
     
     
         26 . The device of  claim 21 ,
 wherein the reference block is a block that is temporally or spatially distant from the current block.   
     
     
         27 . The device of  claim 21 ,
 wherein a size of the first template and a size of the second template are the same.   
     
     
         28 . The device of  claim 27 ,
 wherein the size of the first template and the size of the second template are a pre-determined size.   
     
     
         29 . The device of  claim 28 ,
 wherein the pre-determined size is in an integer sample unit.   
     
     
         30 . The device of  claim 24 ,
 wherein the filter coefficient of the convolutional model is a value that minimizes a mean square error (MSE) between samples in the first template and samples in the second template.   
     
     
         31 . A device for encoding a video signal, the device comprising a processor,
 wherein the processor is configured to:   obtain a bitstream to be decoded by a decoder using a decoding method,   wherein the decoding method comprising:   configuring a first template including neighboring blocks of a current block,   configuring a second template including neighboring blocks of a reference block of the current block,   obtaining a convolutional model based on the first template and the second template,   predicting the current block based on the convolutional model.   
     
     
         32 . The device of  claim 31 ,
 wherein a first color component of samples of the first template and a second color component of samples of the second template for the convolutional model are the same.   
     
     
         33 . The device of  claim 32 ,
 wherein the first color component and the second color component are a luma component.   
     
     
         34 . The device of  claim 31 ,
 wherein a filter coefficient of the convolutional model is a coefficient for at least one sample among a upper sample, a lower sample, a left sample, or a right sample of a first sample of the current block.   
     
     
         35 . The device of  claim 34 ,
 when one or more the upper sample, the lower sample, the left sample, the right sample of the first sample is not included in the first template,   a value of the sample not included in the first template is the same as a value of a sample closet to a sample not included in the first template among samples included in the first template.   
     
     
         36 . The device of  claim 31 ,
 wherein the reference block is a block that is temporally or spatially distant from the current block.   
     
     
         37 . The device of  claim 31 ,
 wherein a size of the first template and a size of the second template are the same.   
     
     
         38 . The device of  claim 37 ,
 wherein the size of the first template and the size of the second template are a pre-determined size,   wherein the pre-determined size is in an integer sample unit.   
     
     
         39 . The device of  claim 34 ,
 wherein the filter coefficient of the convolutional model is a value that minimizes a mean square error (MSE) between samples in the first template and samples in the second template.   
     
     
         40 . A non-transitory computer-readable medium storing a bitstream, the bitstream being decoded by a decoding method,
 wherein the decoding method, comprising:   configuring a first template including neighboring blocks of a current block, configuring a second template including neighboring blocks of a reference block of the current block,   obtaining a convolutional model based on the first template and the second template,   predicting the current block based on the convolutional model.

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